Asymptotic Analysis of Max-Min Weighted SINR for IRS-Assisted MISO Systems with Hardware Impairments

TL;DR

This paper provides an asymptotic analysis of the max-min weighted SINR in IRS-assisted MISO systems considering hardware impairments, deriving optimal strategies with low overhead and validating results through simulations.

Contribution

It introduces a comprehensive asymptotic analysis accounting for hardware impairments at IRS and transceivers, offering low-overhead optimization of power and beamforming.

Findings

Hardware impairments significantly degrade SINR performance.

Optimal power and beamforming can be derived with low computational overhead.

Analytical results match Monte Carlo simulations, confirming accuracy.

Abstract

We focus on the realistic maximization of the uplink minimum signal-to-interference-plus-noise ratio (SINR) of a general multiple-input single-output (MISO) system assisted by an intelligent reflecting surface (IRS) in the large system limit accounting for HIs. In particular, we introduce the HIs at both the IRS (IRS-HIs) and the transceiver HIs (AT-HIs), usually neglected despite their inevitable impact. Specifically, the deterministic equivalent analysis enables the derivation of the asymptotic weighted maximum-minimum SINR with HIs by jointly optimizing the HIs-aware receiver, the transmit power, and the reflect beamforming matrix (RBM). Notably, we obtain the optimal power allocation and reflect beamforming matrix with low overhead instead of their frequent necessary computation in conventional MIMO systems based on the instantaneous channel information. Monte Carlo simulations verify the analytical results which show the insightful interplay among the key parameters and the degradation of the performance due to HIs.